Machine Learning Engineer, Platform Architecture

Machine Learning Engineer, Platform Architecture

Cupertino, California, United States Hardware

At Apple, our Platform Architecture group is responsible for connecting our hardware and software into one unified system. You’ll collaborate with engineers across Apple to design how our technologies work in unison, drive development of our renowned system-on-a-chip architecture and develop forward-looking prototype systems! Our team works at the intersection of ML applications and Apple silicon architecture. We collaborate with SoC/IP architecture, system, software, and algorithm teams to develop integrated, highly optimized solutions for machine learning applications.

Description

In this role, you will explore different ways of mapping ML workloads to Apple silicon and develop performance models/simulations. Your work will inform and validate architecture decisions. You will gain insights on how to make workloads run efficiently on our SoCs and communicate what we learn to software and algorithm teams.

Responsibilities

• Create optimized implementations of ML workloads on Apple silicon including Neural Engine, GPU, and CPU.
• Collaborate with IP and SoC architecture teams to develop performance models and simulations of future hardware.
• Conduct performance studies to inform and validate architecture decisions.
• Collaborate with system teams to create high-level performance models of emerging ML techniques and analyze system architecture trade-offs.

Minimum Qualifications

• Ability to program in C/C++ and/or Python
• Knowledge of computer architecture fundamentals
• Domain knowledge in at least one hardware IP: ML HW accelerators or processing units such as GPU, image/video, CPUs, or similar

Preferred Qualifications

• MS or PhD in EE/CE/CS or related field, or 3+ years of relevant experience
• Experience with ML frameworks (e.g. PyTorch) and efficient implementations of machine learning algorithms
• Experience in optimizing and deploying ML models and/or runtime frameworks in production inference/training environments
• Experience in creating SoC or IP performance models/simulations
• Verbal and written communication skills for collaborating with partner teams
• Ability to prototype algorithms on CPU/GPU/Neural Engine, analyze performance metrics, and create high-level complexity models
• Understanding of compiler frameworks/technologies

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including:
Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note:

Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .

Apple accepts applications to this posting on an ongoing basis.

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